|
|
Absolute deviation, 绝对离差
% a- L9 [7 o! p1 M7 J% d. b: Y3 NAbsolute number, 绝对数
3 |$ p% ]1 Y e) R/ fAbsolute residuals, 绝对残差" a% ]% v K5 [ e. [/ [7 o- @
Acceleration array, 加速度立体阵) D9 @0 ^" Q7 C8 T% {- p* S! l
Acceleration in an arbitrary direction, 任意方向上的加速度* g1 q& C# q2 u9 D* y+ H
Acceleration normal, 法向加速度4 N3 Q) ~5 \& i9 W y
Acceleration space dimension, 加速度空间的维数$ M5 c! ]; ] D) l
Acceleration tangential, 切向加速度6 a+ C9 d% d% H1 j
Acceleration vector, 加速度向量 B# q' c' \0 a) L
Acceptable hypothesis, 可接受假设
" p# B7 Z' K4 w. v5 i" vAccumulation, 累积9 O8 u2 S# {* j2 g4 t) F
Accuracy, 准确度; |; W7 y9 N( w$ |3 s/ Q
Actual frequency, 实际频数
9 @2 C& H0 z+ j% ~! l1 s& ]% R# nAdaptive estimator, 自适应估计量( \1 N0 |) j) s3 y( ]& Z: ~: H0 W1 {" w# J
Addition, 相加
5 h# b s& K: p. i% j5 i" @7 CAddition theorem, 加法定理2 @6 X& `; I9 P3 ]# X- ?0 O4 A
Additivity, 可加性+ o7 \, Y: N8 s
Adjusted rate, 调整率
* Q/ G9 c5 n* z+ P" Z xAdjusted value, 校正值
3 r1 v. z" j) n' aAdmissible error, 容许误差
, c' X2 V. k1 ?Aggregation, 聚集性1 l3 {" e1 y- K$ G2 ~: v5 m
Alternative hypothesis, 备择假设/ l" x7 }% A3 C* J
Among groups, 组间
( r. G7 @3 r% FAmounts, 总量4 ^) j# O9 l i( v
Analysis of correlation, 相关分析
/ p4 N4 f6 r. N# Z. }0 `Analysis of covariance, 协方差分析2 N+ r- o! C" E" e5 _
Analysis of regression, 回归分析) P$ r! t- e! {1 Q9 Q8 P
Analysis of time series, 时间序列分析- z& g. g4 Y1 \! [: ?$ u! o$ y
Analysis of variance, 方差分析
! g$ ^/ o" [9 C& R1 b8 u8 s& J9 IAngular transformation, 角转换; ]: Y8 V- g6 F' _. A* s: S
ANOVA （analysis of variance）, 方差分析) B }/ L% `! r
ANOVA Models, 方差分析模型2 J" i4 R a( ?/ Z
Arcing, 弧/弧旋2 N# z# h# N7 F4 w5 n4 f$ q
Arcsine transformation, 反正弦变换% \& w$ p, F& }- R8 P+ R
Area under the curve, 曲线面积
/ Z+ _. c( v# M6 P6 V- h% c8 \AREG , 评估从一个时间点到下一个时间点回归相关时的误差
, ~2 L/ P$ t2 q" M0 u3 {( bARIMA, 季节和非季节性单变量模型的极大似然估计 ) d6 n$ h/ B4 |. }1 \/ Y
Arithmetic grid paper, 算术格纸2 @; g2 Q3 x. S+ C0 o9 G
Arithmetic mean, 算术平均数
, }# v9 [" u+ ZArrhenius relation, 艾恩尼斯关系$ L* ^% ]7 u7 d2 ]: k
Assessing fit, 拟合的评估
' S( h& a) J" }% ^2 SAssociative laws, 结合律
, w4 ~! T9 [6 H0 N: R& X1 ~Asymmetric distribution, 非对称分布# ~: z( [4 W/ }' u
Asymptotic bias, 渐近偏倚# Z" v' a Q, B# I. {% _$ R6 H
Asymptotic efficiency, 渐近效率
! ]: e) C+ m- _, W3 {Asymptotic variance, 渐近方差& @; w/ W1 T+ p" N$ ?2 x7 k8 u
Attributable risk, 归因危险度6 _9 M; e/ B' i5 g
Attribute data, 属性资料% `# {) G$ _) Q( n: E: s
Attribution, 属性. P* E* ?* x7 w/ y5 Y
Autocorrelation, 自相关' [+ r; d [, x6 ^
Autocorrelation of residuals, 残差的自相关4 U. d7 x! H1 x: J
Average, 平均数" T; R/ U# Y0 f, G2 d. |6 b$ o
Average confidence interval length, 平均置信区间长度3 c0 A7 {2 \' i8 S
Average growth rate, 平均增长率, d1 K" L! _$ b K( q8 ?
Bar chart, 条形图
1 z6 C# K6 ?& J7 C7 U, B# nBar graph, 条形图4 p$ {) n' ~* h$ Z9 u% t; C
Base period, 基期
$ W% V V5 o: P' j7 {8 kBayes' theorem , Bayes定理
. O2 f G; ^, O9 X9 [! rBell-shaped curve, 钟形曲线6 w. B- i- O+ q& d3 |& U
Bernoulli distribution, 伯努力分布! N, {4 D/ r# s2 F; Z
Best-trim estimator, 最好切尾估计量
u; u1 ^- A2 ~Bias, 偏性
: M3 `) G, q& m( X; HBinary logistic regression, 二元逻辑斯蒂回归2 v6 P. b& _0 t" Y; \1 C; E
Binomial distribution, 二项分布
/ Q; z% z' u, ]; t1 w* [4 MBisquare, 双平方5 N8 ~ V$ t* [$ l) T* l& a
Bivariate Correlate, 二变量相关1 ~( @' R& ^1 X3 Z
Bivariate normal distribution, 双变量正态分布- q( ~' S: ~5 x4 B$ X+ j, {2 g1 V
Bivariate normal population, 双变量正态总体
9 I5 V% V+ \* U0 TBiweight interval, 双权区间& ]+ D: a+ L2 K3 D' t
Biweight M-estimator, 双权M估计量
" _7 u% s+ O: Y! `" K/ g9 zBlock, 区组/配伍组
4 F% W# |/ S5 Q6 S+ }" bBMDP(Biomedical computer programs), BMDP统计软件包6 \# ~& Y; W( L( v- P
Boxplots, 箱线图/箱尾图9 w5 s- Z# m3 O$ U f6 C
Breakdown bound, 崩溃界/崩溃点% t, R3 B: B5 T) T
Canonical correlation, 典型相关
* a+ B1 A* D1 Q* u% z7 OCaption, 纵标目1 E# |; {1 E- q4 A) n! e. ?
Case-control study, 病例对照研究, b M- }9 o+ B7 ~" z4 l% V* T
Categorical variable, 分类变量6 h" m) n2 h9 m0 F& c
Catenary, 悬链线2 J6 W1 l0 ? ^9 a+ G* N
Cauchy distribution, 柯西分布
% k/ s8 a% y- `3 ICause-and-effect relationship, 因果关系% P5 z3 |& _' Y2 h% V, K+ G' o
Cell, 单元
0 `' Z3 }1 l" k c9 g0 j1 ]$ MCensoring, 终检0 e$ R) t- Z- K0 l6 d: U2 P' L
Center of symmetry, 对称中心
1 s4 D" |+ o& z% PCentering and scaling, 中心化和定标
3 [: D2 A) P7 {( [# G% ~* PCentral tendency, 集中趋势, m9 n# Z1 W/ }
Central value, 中心值
. C. R: [. {. ^& j$ c! iCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测3 k" R' L6 _: R$ D+ ^3 G% R
Chance, 机遇
0 L- Y. d% C9 l7 OChance error, 随机误差
5 N' d/ u) f( I; GChance variable, 随机变量
2 \5 L8 Z0 l# q8 p RCharacteristic equation, 特征方程
3 r1 G% f6 r" g6 DCharacteristic root, 特征根
) [! f3 }. I/ q4 g( |3 ]5 eCharacteristic vector, 特征向量! K8 @( J& u2 D( x! B) N1 ^+ k
Chebshev criterion of fit, 拟合的切比雪夫准则
( Y7 ?! g9 v& o2 i! I# E0 c$ L# RChernoff faces, 切尔诺夫脸谱图. P2 Q Q1 W7 q- z
Chi-square test, 卡方检验/χ2检验. @. U5 f" g6 c8 u
Choleskey decomposition, 乔洛斯基分解. i) E3 B& C& P" ?4 L! r& m. h
Circle chart, 圆图 4 J( |$ Y" [% A7 E8 z$ i4 A) E" W
Class interval, 组距
& a B( q( H* N( SClass mid-value, 组中值1 R! S3 \' |% n
Class upper limit, 组上限
% W/ a( e, ?( IClassified variable, 分类变量
- ?' a+ D- F* O) [0 h8 \ eCluster analysis, 聚类分析1 w5 l* y$ I: j3 O2 {2 }# X& M! z
Cluster sampling, 整群抽样2 P5 W% L2 F" |% v, c4 e- ]
Code, 代码) t# I' c6 o3 W u4 b
Coded data, 编码数据
( o5 g! D' M+ z7 ^/ Q* @Coding, 编码1 { B2 Q% F; c. V: i% J
Coefficient of contingency, 列联系数3 s0 I0 X! ?; J8 \8 s7 V: ?0 m
Coefficient of determination, 决定系数
6 i* h7 N! w$ d( KCoefficient of multiple correlation, 多重相关系数( u) q i, \4 y; Y$ u% W0 M
Coefficient of partial correlation, 偏相关系数1 n" `0 Z* n3 d0 q' v3 @8 M$ J
Coefficient of production-moment correlation, 积差相关系数
; q, q8 r, U8 {: fCoefficient of rank correlation, 等级相关系数
9 t1 o* A* a0 E2 k$ b) MCoefficient of regression, 回归系数
! S; C* T7 x% j9 Q; O1 pCoefficient of skewness, 偏度系数. N3 q q N7 z6 X, e
Coefficient of variation, 变异系数
3 Z2 p9 x( ~ x b3 L8 x1 Z8 G2 cCohort study, 队列研究/ z% k& m( `6 r: b1 W, M
Column, 列2 B" |; R$ b# ^# e! l& \. t
Column effect, 列效应6 z2 t/ o( g* E1 Q4 ? t
Column factor, 列因素
- c M# P0 i( R0 o+ o' s" jCombination pool, 合并9 S* O% q0 e/ o2 W, m" U8 F- c
Combinative table, 组合表
* }2 V$ ^4 q% C SCommon factor, 共性因子
& m( V% y9 d* i9 C" t; gCommon regression coefficient, 公共回归系数
8 m$ P* I& N0 A& z0 S0 wCommon value, 共同值" i) t; A5 ?# w
Common variance, 公共方差" x& ^( C0 C+ n9 t7 C2 I- B* P
Common variation, 公共变异
6 ]/ D# ]1 d2 v$ ]0 e# SCommunality variance, 共性方差
* }% m$ P7 R) ~1 PComparability, 可比性2 t+ ~( _: U( _ y& p
Comparison of bathes, 批比较
4 V. w0 m8 |# ]! \! E6 @: H* QComparison value, 比较值- V8 P$ f0 a+ j6 N6 r5 @
Compartment model, 分部模型, d1 u9 [/ d; m9 P
Compassion, 伸缩
4 C+ n+ v0 {3 T$ ~4 e$ a5 KComplement of an event, 补事件0 p. c5 L) _7 g0 _" v6 \, d; b1 z
Complete association, 完全正相关' E- U2 E3 F, F+ L( G" f4 a, Z: U
Complete dissociation, 完全不相关
) h; s% o9 ]" \Complete statistics, 完备统计量( B: E$ g9 C" Y5 m, ]8 \
Completely randomized design, 完全随机化设计
' f* d* H5 C' h; T X8 rComposite event, 联合事件1 O" x$ c1 U% l1 i' S S( H; f. w
Composite events, 复合事件. X1 g+ h& I3 H2 O
Concavity, 凹性8 b6 y/ o3 x7 P! o3 V- ~8 _7 K$ a
Conditional expectation, 条件期望
$ K4 o8 O, d% wConditional likelihood, 条件似然
0 U: v' U$ o& z2 j! iConditional probability, 条件概率' C1 a. f* z/ |
Conditionally linear, 依条件线性) O8 S: M& X' U7 }! S
Confidence interval, 置信区间
! {; t. e7 f4 C# x5 f5 z% b' XConfidence limit, 置信限0 d! U: x8 Y2 n& a: Y- ^
Confidence lower limit, 置信下限5 m; ~) D* ^5 p* h# L$ s
Confidence upper limit, 置信上限
, X) N' Z C+ V- f# D, d$ PConfirmatory Factor Analysis , 验证性因子分析
& o6 w+ W& y& i8 F1 Y5 aConfirmatory research, 证实性实验研究
4 A3 }& @2 d5 i! N' Y! LConfounding factor, 混杂因素
" m7 l: x3 I- LConjoint, 联合分析
* w; `/ S& ]8 jConsistency, 相合性, h+ p( L4 x( {* C/ C" T- y
Consistency check, 一致性检验' i+ [- h& x% I1 u. B: Y
Consistent asymptotically normal estimate, 相合渐近正态估计9 Y5 Y% U( T7 \( q" O3 ~! H8 S- D
Consistent estimate, 相合估计: T3 l5 Z4 q8 A; [3 p8 T
Constrained nonlinear regression, 受约束非线性回归
. F" N+ U2 P. p" |Constraint, 约束
8 M& k5 W; x% j5 _0 A8 lContaminated distribution, 污染分布
% h1 P& l" S7 F& w% a! o6 DContaminated Gausssian, 污染高斯分布# P/ j% L9 Y0 Q& ?# h3 e
Contaminated normal distribution, 污染正态分布
* A/ d9 b. H- l0 uContamination, 污染8 Y- N: x+ m8 P0 L- T* Z* R0 g$ F
Contamination model, 污染模型- Q1 l8 e+ w9 Z6 O9 E% s
Contingency table, 列联表
* m8 ^+ r* h. @, o3 \2 lContour, 边界线" K) n/ P% p# e. ]% p Q
Contribution rate, 贡献率1 U+ S( N! o0 w8 ^( a+ j2 @. n! f
Control, 对照
" ? _+ L7 m9 j+ t# g7 r* aControlled experiments, 对照实验0 M3 p6 j' T4 I+ L8 t: m
Conventional depth, 常规深度$ d( Z& y5 {* c7 \- t" i. W
Convolution, 卷积$ O; m( H- t6 j4 n- O+ Q
Corrected factor, 校正因子7 h: V' w; i0 m- }, A
Corrected mean, 校正均值
+ z- p2 j3 }- S+ D4 t5 O& b2 FCorrection coefficient, 校正系数
- w4 v( M. X' ^! I$ hCorrectness, 正确性
: h7 W6 ]% W4 v1 A, ^1 j0 NCorrelation coefficient, 相关系数' I& e( m; l* d$ T7 }
Correlation index, 相关指数 q+ l8 X7 s* E4 _8 k% y
Correspondence, 对应
6 ~8 a& d r- \: l" `, ?4 Y6 t0 kCounting, 计数2 A' y3 s2 ^- k* r5 N$ }2 l8 p7 g& U
Counts, 计数/频数3 P9 V2 S& [7 T+ o$ B
Covariance, 协方差9 e2 j4 u, ?; [4 q6 ?3 C
Covariant, 共变
. l$ k" Z0 S; ?, _# }: R) tCox Regression, Cox回归
8 A5 W" N' q& B# WCriteria for fitting, 拟合准则
; ?% i# V+ u4 w2 lCriteria of least squares, 最小二乘准则, Z* ]& m# m; l+ | `
Critical ratio, 临界比 F& c! J+ _3 n+ x( W7 N
Critical region, 拒绝域
3 h8 m. M5 F; r/ E- f; TCritical value, 临界值0 A( r$ | b0 h% A T
Cross-over design, 交叉设计
5 C% H( @! m. ] q% a7 K% NCross-section analysis, 横断面分析6 }( U: x+ V' T* d7 o+ y5 g
Cross-section survey, 横断面调查
. Y6 Y: }/ M* ?8 b- K) M3 [8 p( bCrosstabs , 交叉表
$ L0 G8 s0 {0 u* M3 e$ ]Cross-tabulation table, 复合表9 }! t- [ k0 S/ d) j/ u! p
Cube root, 立方根
( |- {& T0 Y7 \4 E1 \4 c# CCumulative distribution function, 分布函数( Q+ m9 E7 S0 U5 d# M8 {
Cumulative probability, 累计概率
9 _( W/ w; B- [/ sCurvature, 曲率/弯曲8 w/ w- _- ?) {& d: a' B
Curvature, 曲率
; \' K$ u$ _# L3 @. GCurve fit , 曲线拟和 ( Y! z$ E9 ]+ J9 v! ? i: d4 i
Curve fitting, 曲线拟合
6 v" U2 Z/ }/ SCurvilinear regression, 曲线回归 i# U( i7 {% B7 K) ^$ \9 ^; ~% X
Curvilinear relation, 曲线关系; g" J( q3 t1 ^
Cut-and-try method, 尝试法6 F+ G# d: @- x5 b
Cycle, 周期
, t7 x# i; N3 vCyclist, 周期性5 w( d- V) i' b$ B, o# y
D test, D检验
0 E# o; Y/ |+ `$ xData acquisition, 资料收集/ g8 o: B* ~# M% g. n4 t5 S9 p
Data bank, 数据库( v' t) t$ b, N" W; _+ n# Y
Data capacity, 数据容量
# S: z! w# i% Y! R7 O% p8 UData deficiencies, 数据缺乏' ~& L6 ?, y' s
Data handling, 数据处理
$ G6 q2 N3 k) ?9 aData manipulation, 数据处理
5 o _6 x/ }: N I) T& \3 NData processing, 数据处理' @ ]+ X2 H2 L v* C
Data reduction, 数据缩减" z3 x1 N3 F& ], v$ Y/ k
Data set, 数据集" U7 d0 B8 q) L
Data sources, 数据来源: L8 H4 R V; z5 d
Data transformation, 数据变换
4 j& V4 K6 v( x# m( n& p3 z* w% gData validity, 数据有效性, v5 J7 y2 F/ J6 B# f
Data-in, 数据输入 u5 V% D, x* d7 ^" D, o N
Data-out, 数据输出' k6 T! J+ {# l U
Dead time, 停滞期/ ?+ L# w3 u* Q) Q: W/ o4 p
Degree of freedom, 自由度& F. G" @3 D+ Z# \( b$ X
Degree of precision, 精密度, ]- e0 N& T/ K9 e$ h
Degree of reliability, 可靠性程度) X9 |6 e* U' C/ t2 I1 E
Degression, 递减
& D2 r( l, k( jDensity function, 密度函数
" Y8 w2 s% }6 [( C0 W9 j. f# bDensity of data points, 数据点的密度
: B& m2 I! H& ^* GDependent variable, 应变量/依变量/因变量' J7 Z" @$ G8 A: M5 m
Dependent variable, 因变量. U5 L- f5 Y/ f. ]
Depth, 深度4 t1 s4 y$ E; _( x& u& F3 X
Derivative matrix, 导数矩阵
4 ]$ z2 {6 \7 B; N& N9 b0 NDerivative-free methods, 无导数方法
" D. D; F+ ~! ]: k. ^$ n3 KDesign, 设计
3 o7 m3 z3 a9 H0 R& I1 ^% l* E' QDeterminacy, 确定性
; S$ } R5 s* P0 UDeterminant, 行列式5 [7 k+ `& Q4 M5 G- n O) t# v% Z
Determinant, 决定因素7 I$ ]$ T0 W$ [$ s
Deviation, 离差1 i7 o* O5 b: o! P" H
Deviation from average, 离均差
4 b c$ }% b# r$ M7 nDiagnostic plot, 诊断图
9 m8 t8 s7 ~# R7 i9 ?4 XDichotomous variable, 二分变量% V" ?- v! `$ C" f; Z
Differential equation, 微分方程
' V: e6 a$ E5 K) ^$ a) ]3 ]# |Direct standardization, 直接标准化法) ? ^# k% Z$ I4 d; y' F
Discrete variable, 离散型变量
! H! ^) J; m: w0 X' uDISCRIMINANT, 判断
( ~" r5 B# @2 ?3 A' a& ?$ x6 ODiscriminant analysis, 判别分析0 _" x: {$ q8 X, i1 L8 I2 l" \/ t
Discriminant coefficient, 判别系数
0 Z- a$ u1 ~- Y( HDiscriminant function, 判别值
( u9 ^* n' Z: G' a B' C% D6 K9 G. \Dispersion, 散布/分散度
6 @) |2 c% b0 C$ VDisproportional, 不成比例的
4 H0 t) G: i; j* `! ZDisproportionate sub-class numbers, 不成比例次级组含量
' s% _ m- L+ }Distribution free, 分布无关性/免分布
- e% m1 _8 }9 ?Distribution shape, 分布形状6 l- L8 g8 {5 v; F) S
Distribution-free method, 任意分布法
$ F- e& S$ c: S& ]$ Z2 qDistributive laws, 分配律; S8 y% t3 x4 W8 b3 V" {8 C
Disturbance, 随机扰动项
, \1 G# f. X) K" M6 |5 ZDose response curve, 剂量反应曲线
. w' h7 W6 I6 n5 t5 DDouble blind method, 双盲法5 x+ n9 f% E8 s! l1 A
Double blind trial, 双盲试验- ]( D5 f3 |5 t6 o* W) a" ^! M
Double exponential distribution, 双指数分布0 N( T4 y& r% R' B9 a
Double logarithmic, 双对数
: x5 c8 Q( b# mDownward rank, 降秩
# ^) w, R, Q8 E7 Q: Q- A% g% |8 NDual-space plot, 对偶空间图5 H) m7 n) y6 T6 G, y9 B
DUD, 无导数方法
8 i& @2 {; f) u' O1 J# lDuncan's new multiple range method, 新复极差法/Duncan新法
0 G$ X4 f6 d1 _! W1 _Effect, 实验效应
# g" w3 U, A0 l! bEigenvalue, 特征值9 E7 |: ^3 ~1 v2 L9 ^+ }' I. R
Eigenvector, 特征向量
1 x7 b- I3 {1 X5 k' cEllipse, 椭圆
. ?9 {" V( A$ qEmpirical distribution, 经验分布
8 N' \! T; i. v' REmpirical probability, 经验概率单位
1 W5 |7 K3 x+ W6 B7 `* aEnumeration data, 计数资料" W* B7 a! s \ r
Equal sun-class number, 相等次级组含量+ c3 R& t/ Y0 L w, l, m
Equally likely, 等可能* k, @% F9 V: V. Z& h
Equivariance, 同变性
* _1 Q6 u! O2 B# J& y* Y, ]7 IError, 误差/错误
0 ^; F5 ~) }) `3 M! S6 {% vError of estimate, 估计误差
* [9 U5 e" E1 _ @0 c; kError type I, 第一类错误
' n' v/ k6 I! x/ ~$ l `Error type II, 第二类错误
3 G E9 O/ H' y+ O0 v uEstimand, 被估量
; i8 h \0 |2 T) |/ w MEstimated error mean squares, 估计误差均方
( N% p* O! h! HEstimated error sum of squares, 估计误差平方和$ \' z: ^9 h {+ W$ Q
Euclidean distance, 欧式距离
( e* {- B1 N- i. M+ d9 V4 c# }/ Z6 bEvent, 事件
. R9 b# f3 a! q8 yEvent, 事件
* y3 c+ Y( E7 ]8 U# [3 Y$ g; HExceptional data point, 异常数据点
; {1 ~) e* m* K0 w T6 ^Expectation plane, 期望平面
$ U) g3 k" S" p, `( v' GExpectation surface, 期望曲面
8 Y) L8 |) F& c$ [# L, X9 {# LExpected values, 期望值
; G8 \; u; F, N1 G5 }# z- M) K+ fExperiment, 实验0 F+ @: t8 T4 y# k' ?
Experimental sampling, 试验抽样& S! G, u" t8 z8 L+ C" _
Experimental unit, 试验单位7 `4 [5 g7 d7 P( ^# d
Explanatory variable, 说明变量
; Q g" [4 ?8 G1 P; w% ` QExploratory data analysis, 探索性数据分析& R5 e' V$ A9 A/ A
Explore Summarize, 探索-摘要) `! O1 X( W2 J; {4 L6 W
Exponential curve, 指数曲线
( x+ A6 P8 O* H+ V, i( ~Exponential growth, 指数式增长
6 a Q, h7 Q# \/ ~+ jEXSMOOTH, 指数平滑方法 / K c; V4 x& ^! y" d2 T( n5 X( h
Extended fit, 扩充拟合' u/ K' b: g" h. X6 Y
Extra parameter, 附加参数! ^2 b2 Y; O7 ]% U$ @
Extrapolation, 外推法# V0 T1 Z+ v, X+ ]* h1 \9 m
Extreme observation, 末端观测值0 t/ I! O1 o+ ?) g1 |
Extremes, 极端值/极值
/ H. B) p0 M4 E& ]5 |4 ^F distribution, F分布
: G C0 i+ E" N: DF test, F检验
1 B1 @& R/ I' d: W2 R& F& q8 U2 JFactor, 因素/因子( g w, v" E4 G- S% G4 ^
Factor analysis, 因子分析' }5 U- B S- Y
Factor Analysis, 因子分析/ d: i8 {9 u1 J, k- y" J S0 \
Factor score, 因子得分 4 h! s' b1 s1 T
Factorial, 阶乘
% K$ J7 v0 d) m l9 sFactorial design, 析因试验设计: ?3 l9 ~* A) }2 p
False negative, 假阴性
1 O! i, \# ~9 X: w- `9 C* |1 HFalse negative error, 假阴性错误
" M8 N) C) a* _/ b$ V6 V9 N$ m9 cFamily of distributions, 分布族
2 W& w; _) z4 V- r% r9 Z) dFamily of estimators, 估计量族
* e B8 K+ G: ?7 KFanning, 扇面
7 q$ E" a, `3 t: xFatality rate, 病死率
( E% }' O2 g5 a- h; W H2 lField investigation, 现场调查; U! o8 w1 i. z! B( @
Field survey, 现场调查3 H% k2 T+ E! |7 [5 q
Finite population, 有限总体
! `/ u0 P4 a* S! _/ MFinite-sample, 有限样本
4 C! Q3 x4 ? h! AFirst derivative, 一阶导数1 \% p8 R% k' M" |& d
First principal component, 第一主成分
) H0 e9 M5 J4 N2 l% G& v; t c3 I0 QFirst quartile, 第一四分位数3 O4 i x# G* k) J- p" o, J, s$ F, V
Fisher information, 费雪信息量% ?9 U# E$ v2 f- @2 K
Fitted value, 拟合值2 c& u5 K3 G" ^' e8 F: S
Fitting a curve, 曲线拟合
0 p+ k" p' r2 |0 z8 ]Fixed base, 定基
q1 }! J! P1 w9 V1 F; EFluctuation, 随机起伏
: F' G [/ v ?- o: A; ]9 \ A, nForecast, 预测8 X0 ~' C6 |9 H2 h4 \8 X
Four fold table, 四格表. h: O/ r, X$ Y& h' H
Fourth, 四分点
; x3 N4 y5 x' Q7 ~. aFraction blow, 左侧比率
/ g# }4 k7 q% ]( a! C) qFractional error, 相对误差
6 r: d8 b. K# ~! ^! R9 @. L; RFrequency, 频率: E5 I% W3 v. |; Y! Y. t9 j
Frequency polygon, 频数多边图5 r1 V. ?, P8 n" k# e1 F7 r
Frontier point, 界限点1 B! O& a, j+ L- I& h0 @; V
Function relationship, 泛函关系; M: |2 E5 C! W' }
Gamma distribution, 伽玛分布 b) i" \7 T" _/ _# \( v
Gauss increment, 高斯增量
6 Q/ k! q6 m; c+ ~4 q, _/ Z" J8 eGaussian distribution, 高斯分布/正态分布
6 ^- F$ h1 a* K' {- P' O3 a3 LGauss-Newton increment, 高斯-牛顿增量
; ]" b0 x$ I4 R5 tGeneral census, 全面普查' c: T$ p W) G% f
GENLOG (Generalized liner models), 广义线性模型 h, o6 m& k4 N$ s4 }' t5 y
Geometric mean, 几何平均数: R- V1 B; d2 f3 |( z
Gini's mean difference, 基尼均差0 c4 L* P! J- Q4 H& F# @
GLM (General liner models), 一般线性模型
4 Q2 j) d. S( I+ u4 X1 G6 tGoodness of fit, 拟和优度/配合度% D" R# i3 w# C( N+ C4 q; K. i
Gradient of determinant, 行列式的梯度: F( S( b8 s- e8 ], Y
Graeco-Latin square, 希腊拉丁方
X# S$ ^) O( E' r5 @6 L+ j# u* zGrand mean, 总均值8 Q5 c! J- i) C1 ?' \9 Z) ~
Gross errors, 重大错误
9 H8 O. r+ t3 @% l) {% ^Gross-error sensitivity, 大错敏感度
: N- I9 S) T# \6 T( c1 a' x+ [# e! ZGroup averages, 分组平均
% @ y5 P a6 _Grouped data, 分组资料: d3 a) {: g* v4 P4 M6 \ S2 v6 [! P
Guessed mean, 假定平均数4 Q. R6 n" r0 K0 }
Half-life, 半衰期7 K& w- k C; Z4 N& @
Hampel M-estimators, 汉佩尔M估计量
^0 ~8 w. }0 k: {Happenstance, 偶然事件
# c" h: d0 j: ?Harmonic mean, 调和均数7 Q4 ] |! V% S# b- X5 k
Hazard function, 风险均数, z1 u: ^5 z" R4 [, l
Hazard rate, 风险率
/ x3 [) u% X. R( P! ~Heading, 标目
7 ^& `+ B/ j$ D# BHeavy-tailed distribution, 重尾分布
, t' o" j" H9 O; C5 R6 U' R1 q1 nHessian array, 海森立体阵0 e2 o! I2 i; a; a: b5 S& j
Heterogeneity, 不同质
8 f Q5 p) i+ M" B: H4 EHeterogeneity of variance, 方差不齐
; K& _+ l1 _) Q, \6 M" bHierarchical classification, 组内分组6 j! P7 d& v j5 U, U' _
Hierarchical clustering method, 系统聚类法4 D+ Y' D6 F& T1 r
High-leverage point, 高杠杆率点
\. x/ q1 e$ w1 k7 ]HILOGLINEAR, 多维列联表的层次对数线性模型
+ _$ s h' `* ?. ^Hinge, 折叶点
( z3 C% Q/ F- F. g9 k* JHistogram, 直方图
. B F/ u9 d# P) K8 W6 gHistorical cohort study, 历史性队列研究
( X" v1 c$ m" O5 v# @0 oHoles, 空洞4 w4 ^* j' b$ @* C5 J
HOMALS, 多重响应分析, r: D* M% h r* Z
Homogeneity of variance, 方差齐性) [% D/ K8 N, {0 ^5 p! X
Homogeneity test, 齐性检验7 V& b' o" U, Z3 @/ x
Huber M-estimators, 休伯M估计量' K5 O+ _- ^4 j7 {! E
Hyperbola, 双曲线
4 r; U5 z) ^: N0 e- y' ?* w- O# IHypothesis testing, 假设检验; N w9 f2 d0 @! [1 `
Hypothetical universe, 假设总体% n8 ^1 p. I- d7 v+ N1 O
Impossible event, 不可能事件& t7 w4 K4 S2 W+ c8 j ^
Independence, 独立性6 e5 X |, M' \3 v
Independent variable, 自变量
8 N, _5 P7 r6 P C3 j* pIndex, 指标/指数
9 {9 Z3 z7 @% k; `7 B0 R; HIndirect standardization, 间接标准化法
r. L6 P* I0 I% m: @Individual, 个体
9 J" x: g. M: A/ z4 Y2 [Inference band, 推断带, f/ G# M' v% A" K1 H% L
Infinite population, 无限总体
2 Z$ {& n' {' e' n2 v# N0 ^Infinitely great, 无穷大# y/ B. U4 @/ h" z0 z# Y
Infinitely small, 无穷小3 C C# g, y6 N
Influence curve, 影响曲线8 y/ t% d- x! E& ~8 \+ p& I- h+ m
Information capacity, 信息容量$ N% b# X. m& o3 _& O: p+ E
Initial condition, 初始条件# P; {% l4 W3 t0 I% L
Initial estimate, 初始估计值7 ?& L; k$ `* Y8 r
Initial level, 最初水平# o! ~9 E& Z8 V( w
Interaction, 交互作用
( I0 }8 V9 Z2 r0 t( z, _Interaction terms, 交互作用项" X9 ^3 R! ^. i5 d. [1 N% w; T# d
Intercept, 截距
5 i- _/ I2 F: ~8 U- OInterpolation, 内插法
" |6 b/ D( c) `6 V* `Interquartile range, 四分位距
2 b3 [7 _: z6 q5 m. l2 E+ G" zInterval estimation, 区间估计- S) _9 _# l. x& M; r' | C" T# E1 E
Intervals of equal probability, 等概率区间
. T% H- ]" }3 U$ c2 ]4 EIntrinsic curvature, 固有曲率/ ?) e, }( q f- m1 N: B! V
Invariance, 不变性0 S3 X3 P& _! _. W0 k
Inverse matrix, 逆矩阵 T! [$ n2 N. c C% y
Inverse probability, 逆概率+ A1 O/ z. ^/ G
Inverse sine transformation, 反正弦变换. p. F) f" }2 z0 W2 i) n& H
Iteration, 迭代
6 c. [. s& t, h$ j* ?Jacobian determinant, 雅可比行列式
$ c$ B4 z! A4 O/ T- ~Joint distribution function, 分布函数5 Q! v/ s9 F$ n/ G+ f; X: R
Joint probability, 联合概率6 J1 Y: a8 `( u$ j
Joint probability distribution, 联合概率分布$ s8 y5 f, ]3 q
K means method, 逐步聚类法
! o; R! D) R/ ^8 P7 y+ M; a; b, c' `# YKaplan-Meier, 评估事件的时间长度
, j/ T" P7 \# ^: U, d) o6 AKaplan-Merier chart, Kaplan-Merier图
6 m j* I" y2 N7 e/ r& @/ WKendall's rank correlation, Kendall等级相关
6 c" S3 F/ J2 S+ W* ?8 sKinetic, 动力学
& l# M' k- h# E& h. M6 }" bKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验" S5 I. j; l! V+ L8 D$ n' Y
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验( s8 l/ j" p, A2 S, A6 M% N& Q7 m
Kurtosis, 峰度- L# V6 ~! |+ i: f
Lack of fit, 失拟! N5 z+ U- R. {8 H
Ladder of powers, 幂阶梯
, J D0 h: N. bLag, 滞后0 |" y3 Z6 @ c
Large sample, 大样本
. Q: N4 @3 x' c) ^Large sample test, 大样本检验
% @, c- M6 }: M& `) z1 [Latin square, 拉丁方
C2 M7 @& Q3 vLatin square design, 拉丁方设计
+ g [4 H# L1 D# U- GLeakage, 泄漏* D# ~8 i& Q# x" x- R6 a
Least favorable configuration, 最不利构形+ {1 p$ T) ^/ j& X
Least favorable distribution, 最不利分布
9 f& q, f/ P# b3 @) t0 BLeast significant difference, 最小显著差法
. l0 W+ O% w# n# ^/ `& E0 eLeast square method, 最小二乘法. ^" e4 m1 G& b+ A; ]) @* T- ~
Least-absolute-residuals estimates, 最小绝对残差估计
5 H1 L. Q7 y( f7 jLeast-absolute-residuals fit, 最小绝对残差拟合2 V0 X8 a0 ?' {0 K( ~$ S
Least-absolute-residuals line, 最小绝对残差线
4 k+ s0 }6 h# n& h1 k) WLegend, 图例: c# j' n. Z# G# K5 J
L-estimator, L估计量' J$ T% b6 \3 `9 f; P+ o
L-estimator of location, 位置L估计量4 U; w0 I& ^, M9 K( A# Z! I- \
L-estimator of scale, 尺度L估计量, @$ p' }4 m; T y; k1 E
Level, 水平
/ X% p7 B4 b1 m" n" X9 X' R' wLife expectance, 预期期望寿命4 c# C" T1 s9 ?) @& {3 {4 n
Life table, 寿命表! Q. H- j" W% K8 W5 s
Life table method, 生命表法% R& n" M$ o' e' A) H4 n* t) m% S! M
Light-tailed distribution, 轻尾分布
0 D8 e: e& k% u* P2 W' u6 c7 ]) }Likelihood function, 似然函数* Q5 b7 b! B6 ? L# B. t
Likelihood ratio, 似然比
' N. b" D- `6 v& ?line graph, 线图
' b; a! l, l# h* c5 U6 f' E1 C/ [Linear correlation, 直线相关
$ I; M) b8 r/ D/ N" C( d- ?; C+ i' [Linear equation, 线性方程
- o: g) ~2 M* @5 @Linear programming, 线性规划9 B; A. _+ j0 p- j, q7 w
Linear regression, 直线回归; \4 M4 W; G) A
Linear Regression, 线性回归7 w$ h) s6 G- Z8 u$ G4 R x* a
Linear trend, 线性趋势
2 G/ B- l/ z; H2 nLoading, 载荷
* S* d5 l' E; w: |. R, dLocation and scale equivariance, 位置尺度同变性- E9 D0 g( t7 `8 E" e" s5 I u: A0 E9 u
Location equivariance, 位置同变性
+ S7 r3 c$ {1 l1 A- @2 tLocation invariance, 位置不变性, l/ h" }" J* T
Location scale family, 位置尺度族; x0 E( x! V. m. b1 A
Log rank test, 时序检验
5 \/ k5 l& E! R/ O# U. I' gLogarithmic curve, 对数曲线
9 X! y: W# t1 g, f3 n, L# E9 YLogarithmic normal distribution, 对数正态分布
9 q: X) h- i) fLogarithmic scale, 对数尺度: _' U$ a- i7 R. z1 H) T7 R$ B. }" L
Logarithmic transformation, 对数变换
$ @1 _" C* }, E. ]) q& rLogic check, 逻辑检查
) e' N! ~7 q5 ILogistic distribution, 逻辑斯特分布* E- N. u4 x' L
Logit transformation, Logit转换
- f3 o: ~9 `+ F6 W w4 }# ~LOGLINEAR, 多维列联表通用模型
" C% @4 y; [! A* e0 l9 A, |6 _Lognormal distribution, 对数正态分布
1 n2 ]" i( Q5 ^5 y% D* A; Y3 }Lost function, 损失函数' ~3 V W3 r7 g; P( ?
Low correlation, 低度相关
" H1 _: J- R- U2 Q% I G( N3 gLower limit, 下限
, T/ J* W2 D& n8 S6 O. ALowest-attained variance, 最小可达方差
" l* P. l2 J2 S/ P/ s2 cLSD, 最小显著差法的简称( [6 U8 r; h& b& B5 w
Lurking variable, 潜在变量6 ?% e( H- w* I% L
Main effect, 主效应' s) p2 y3 r: h3 M
Major heading, 主辞标目
; Q# f( u9 T- f3 D; uMarginal density function, 边缘密度函数
9 |' ], `2 G2 o& ~) m: zMarginal probability, 边缘概率
, W. u6 _3 z% ~' D6 B/ J2 B V: g& a3 UMarginal probability distribution, 边缘概率分布
5 ~! z$ Z* K7 ~8 e2 U C) TMatched data, 配对资料4 j0 v: A2 t( d- v( z8 V
Matched distribution, 匹配过分布+ m" W9 g7 W6 L0 G& l
Matching of distribution, 分布的匹配( v' q9 t- Q' H# C8 s) @7 w" e) j; u
Matching of transformation, 变换的匹配
3 C0 }; b; {( G' h) C2 dMathematical expectation, 数学期望
$ P/ ]6 c2 J% {' a) r8 n+ W' YMathematical model, 数学模型
, X& b6 b/ R. OMaximum L-estimator, 极大极小L 估计量
8 w# _: K1 m3 ^" g5 |( } iMaximum likelihood method, 最大似然法
$ l5 M4 z) N* P. q; X' p$ M- ] ~Mean, 均数# v% J. Y' g# y/ U3 Z2 O
Mean squares between groups, 组间均方
7 R0 d1 x% K9 X" Z) H1 e) O' c4 \Mean squares within group, 组内均方8 P& p5 _, N+ s0 t5 M
Means (Compare means), 均值-均值比较
0 X1 `* L1 _; H& x9 x rMedian, 中位数
( B0 h- S6 e+ AMedian effective dose, 半数效量+ b$ X' J! b3 u+ N M
Median lethal dose, 半数致死量
& ~5 I+ G/ Z% A' E4 JMedian polish, 中位数平滑0 Q9 a, y, ~) L
Median test, 中位数检验/ y" {$ ^% N& E# ~
Minimal sufficient statistic, 最小充分统计量0 I* u3 d9 z1 C; K; f& T! G* i6 @
Minimum distance estimation, 最小距离估计& L% j& U2 k' g1 q* E
Minimum effective dose, 最小有效量
8 `9 O/ l7 N/ l6 M, C1 y) MMinimum lethal dose, 最小致死量
$ Y: `' {4 x3 {. `3 m$ v/ s* f( U9 AMinimum variance estimator, 最小方差估计量
4 r ]. T# ~. H! C" n5 r7 x- f+ eMINITAB, 统计软件包: Z5 j# l# l3 S6 l- [' V
Minor heading, 宾词标目
; t) P9 q7 I7 x! ^" r) H/ iMissing data, 缺失值. H' }( N+ @1 {
Model specification, 模型的确定
2 X+ }+ H) `: xModeling Statistics , 模型统计
% S- R2 S4 k% J2 S) @' Y" U' ^& xModels for outliers, 离群值模型& S8 K* k" Q6 z+ y' ^5 `
Modifying the model, 模型的修正
$ c% l- I7 ^1 q7 |Modulus of continuity, 连续性模! U/ _: |) J0 R. g0 x, F) r& t' _
Morbidity, 发病率
: Z2 m. A m L* X$ _& a. ]7 DMost favorable configuration, 最有利构形3 v, Q+ p' k, Z. u0 `3 P, K
Multidimensional Scaling (ASCAL), 多维尺度/多维标度2 e& [- S( G4 ^8 W9 h: {
Multinomial Logistic Regression , 多项逻辑斯蒂回归
- Z' o/ N1 g# ^Multiple comparison, 多重比较
7 a! P7 `, K6 h1 H: }Multiple correlation , 复相关% L$ w# s7 h5 H
Multiple covariance, 多元协方差 K# h$ ] b9 t
Multiple linear regression, 多元线性回归8 }6 q" R7 O" @. s
Multiple response , 多重选项0 i2 E4 r/ A4 a$ V
Multiple solutions, 多解
/ G6 w. v- o) H: _Multiplication theorem, 乘法定理8 k5 |! W; j B
Multiresponse, 多元响应
' N5 A$ f1 o! P; AMulti-stage sampling, 多阶段抽样
! Z6 W9 P- [" C- UMultivariate T distribution, 多元T分布) I, R3 Q. Y* P9 e" A7 l5 e2 j
Mutual exclusive, 互不相容0 v2 b; s* f3 k( T* v
Mutual independence, 互相独立& r+ u9 ~0 C& B6 X& B
Natural boundary, 自然边界% Y) P2 V( J4 M3 Q* a2 G
Natural dead, 自然死亡3 u" V; j8 c/ ], Z% K( J$ `, C" g$ R8 ]
Natural zero, 自然零
0 @2 @) h- W2 Q1 K( HNegative correlation, 负相关0 P }2 Z3 P3 r- {0 o
Negative linear correlation, 负线性相关: C" [# R0 p8 j" H; q
Negatively skewed, 负偏% A$ I9 z, z% c- i0 |5 q
Newman-Keuls method, q检验: X$ A5 ]/ U8 o2 i. d9 h. i
NK method, q检验
7 O" W+ c( K( R& X; A: PNo statistical significance, 无统计意义, ^: Z @& I8 ~ J
Nominal variable, 名义变量
$ Q7 n1 O0 h5 G- ]! X+ i* oNonconstancy of variability, 变异的非定常性
* Z/ Q/ b+ e- ^. x g3 B* x1 sNonlinear regression, 非线性相关) h; D* g# T9 g4 `! N: f' M1 l$ }
Nonparametric statistics, 非参数统计
! e1 G3 Q' N* `# RNonparametric test, 非参数检验* c. H! _4 |; h3 A4 M8 B
Nonparametric tests, 非参数检验( Q/ l3 {0 d9 l; Y+ D
Normal deviate, 正态离差! L. [/ ~* U3 ? p# v
Normal distribution, 正态分布1 \6 d1 r' i5 b' L2 t
Normal equation, 正规方程组
. P# z- H8 o+ ^; D3 ~5 W8 D6 oNormal ranges, 正常范围- x# D$ j+ |- H+ |4 Q1 {9 D1 z
Normal value, 正常值
5 g, Y1 G1 @. j# w5 t+ ^Nuisance parameter, 多余参数/讨厌参数
! Z1 v9 H% \! w+ T3 x; S$ BNull hypothesis, 无效假设
: m* `( I8 F" INumerical variable, 数值变量1 e: j1 @9 T! ]6 W( T
Objective function, 目标函数& l! k' l: s) V
Observation unit, 观察单位
' k3 O: U& L# ?: v$ i6 gObserved value, 观察值
6 l) I( o* u- _% |% m# y1 \( v6 d5 UOne sided test, 单侧检验
; k4 r( ~7 n) B' IOne-way analysis of variance, 单因素方差分析5 |4 N J) p0 `9 y: y2 U6 R! q( J
Oneway ANOVA , 单因素方差分析+ v6 Z3 y9 r2 n+ H1 K
Open sequential trial, 开放型序贯设计
# [0 f! a6 @6 }; G C* {9 x- uOptrim, 优切尾
! y+ t8 t8 |( {' S, Q b6 nOptrim efficiency, 优切尾效率
2 G% J$ v3 F) M* ], h, pOrder statistics, 顺序统计量
( f- J" [2 [4 Z: |0 P, P/ lOrdered categories, 有序分类
8 Y3 P8 f- ]8 n9 ~Ordinal logistic regression , 序数逻辑斯蒂回归
( J! I. _9 c( o+ H& `Ordinal variable, 有序变量
, U" J! w! a6 H7 i- uOrthogonal basis, 正交基
- z1 b D7 X' ]: e0 {- p* `- _, G% BOrthogonal design, 正交试验设计
0 |9 G3 k% ^$ c1 T9 u8 U" HOrthogonality conditions, 正交条件
$ d' y" w2 ~6 t) LORTHOPLAN, 正交设计 * r# B q& R9 ]! {4 I7 n8 Q1 R7 x
Outlier cutoffs, 离群值截断点) I" N; I2 ^+ c- Q" Q
Outliers, 极端值
/ Q/ b1 A) V- c% {OVERALS , 多组变量的非线性正规相关
6 g a/ J, p- n- D+ JOvershoot, 迭代过度& Q6 P( ^3 g- l4 u
Paired design, 配对设计
6 F% Q: i3 n1 y! y$ l& `) b lPaired sample, 配对样本
0 \ P+ Y+ d. y. |& D) FPairwise slopes, 成对斜率
9 S$ K. I: w m9 M$ ~, }Parabola, 抛物线
! Y1 I0 L& Z8 Z+ F6 i9 V4 d' ?$ IParallel tests, 平行试验
) @/ k- Q$ U9 O- v+ o; y3 jParameter, 参数; l; B% b. R) D
Parametric statistics, 参数统计 \7 Z) @$ \+ D7 A
Parametric test, 参数检验
; H1 b& R: A+ ?" HPartial correlation, 偏相关
/ R& x( c: S; w/ \( }- PPartial regression, 偏回归7 y, z2 r( S2 K/ \" d
Partial sorting, 偏排序3 i \ M: S8 o# D0 C7 A
Partials residuals, 偏残差% u: A, W9 E& _* a6 Q8 b8 a/ \
Pattern, 模式
( H" f3 Y4 m, h( l1 BPearson curves, 皮尔逊曲线
$ N& M% \: y e, ZPeeling, 退层+ L2 ]0 ]$ A! ?/ R- T9 S
Percent bar graph, 百分条形图; t5 g( b8 w# J2 Z
Percentage, 百分比0 d# b2 Z: M6 C: ], Y# e
Percentile, 百分位数' I: t" ~9 d k+ J) K" c" r
Percentile curves, 百分位曲线
. H2 S6 a9 _' B r0 F+ OPeriodicity, 周期性
3 \2 _+ D9 N1 R! C& N& t( SPermutation, 排列1 F9 I1 S- ~2 _+ D- @
P-estimator, P估计量, @" M+ S7 p# @1 d" Q- q }- H
Pie graph, 饼图
* n9 w0 V' u$ P( OPitman estimator, 皮特曼估计量/ V: ~2 B. H+ W" u- Q
Pivot, 枢轴量
' |0 B# o1 s; wPlanar, 平坦
6 a5 A: l: Q, D5 q* [/ KPlanar assumption, 平面的假设
. Z9 V& d4 N! H" x* m3 R$ C8 ?6 l! HPLANCARDS, 生成试验的计划卡
4 n$ C% ]/ M6 ?+ KPoint estimation, 点估计2 @8 O) v/ T# j. C! o: M4 r
Poisson distribution, 泊松分布
, H, v- `9 x1 b% B) T! Q: g/ LPolishing, 平滑 e5 c/ t' N7 }4 I, d" }1 s
Polled standard deviation, 合并标准差
2 I+ F1 ~$ [0 p3 H/ bPolled variance, 合并方差
' A/ }, O" o4 Y; Z! mPolygon, 多边图; P- C/ @4 p1 w" M# a! n
Polynomial, 多项式
% `6 Q# v6 Q( T8 pPolynomial curve, 多项式曲线
8 r1 V' l( g8 l4 T* TPopulation, 总体 B/ K/ q' s4 h$ U2 @
Population attributable risk, 人群归因危险度/ a( \, n2 ^ c
Positive correlation, 正相关$ `. C! _/ a4 `* F
Positively skewed, 正偏7 n9 |/ R7 G/ n6 J" i
Posterior distribution, 后验分布
" Y; j5 a& [$ r8 }8 g7 }! P: JPower of a test, 检验效能8 p6 Z" w% X& }. D: o
Precision, 精密度" h2 {* a2 D: c l7 C
Predicted value, 预测值
/ v7 d' t x9 d. zPreliminary analysis, 预备性分析9 A } q- t6 T. A9 l2 b6 F
Principal component analysis, 主成分分析' y6 H6 f* K, U, N. k
Prior distribution, 先验分布5 [2 ~, z, ?) r& v9 p1 v
Prior probability, 先验概率
' v4 P+ K; E: v+ HProbabilistic model, 概率模型
( f1 X8 C# [, H9 U8 D- D# a7 Q2 Iprobability, 概率5 J: Y# D9 T8 z/ Z! c! e! J# M
Probability density, 概率密度9 A/ `/ h5 e6 X- A/ s: ^
Product moment, 乘积矩/协方差
# D* q; {$ j) P" w' @Profile trace, 截面迹图. |1 Y m9 C: n& } |5 ~! F
Proportion, 比/构成比+ i6 h! z# Y% {) v
Proportion allocation in stratified random sampling, 按比例分层随机抽样
9 H4 R* F# F5 F4 ZProportionate, 成比例
1 d9 N' c9 P0 c5 GProportionate sub-class numbers, 成比例次级组含量
8 z- E9 t6 q" pProspective study, 前瞻性调查
4 `4 e5 G8 E% f( \" k2 ^9 SProximities, 亲近性 : |- u7 m1 Y* ~% q8 K+ w5 h
Pseudo F test, 近似F检验) Z4 j$ j# }' P
Pseudo model, 近似模型
' y% y1 s6 u2 ^& HPseudosigma, 伪标准差
8 ?6 b" \0 b$ SPurposive sampling, 有目的抽样! ?# Z5 f6 C* w* B0 O+ _
QR decomposition, QR分解! u' k: V9 l8 M" A7 S- r6 _
Quadratic approximation, 二次近似
4 \( u: |! C+ ] OQualitative classification, 属性分类
( _4 i9 O9 v% F3 p$ fQualitative method, 定性方法
i3 l- M* y3 h# KQuantile-quantile plot, 分位数-分位数图/Q-Q图
- h& \0 U8 I# w' i" rQuantitative analysis, 定量分析
+ y* o* y4 C0 i8 l3 ]: QQuartile, 四分位数
5 [4 l( j, J& v# n& p; B5 H+ \Quick Cluster, 快速聚类. A( U( W+ y" J
Radix sort, 基数排序
- g# A- P# ~: {* xRandom allocation, 随机化分组
7 U5 l/ [: W DRandom blocks design, 随机区组设计
( `4 Q4 b6 K6 z6 {3 K- U% vRandom event, 随机事件
. ~( B( [% H# s+ f9 h4 [& h' v4 |6 oRandomization, 随机化: e3 C: d0 n$ @5 A: ]3 c
Range, 极差/全距2 Y# d5 t% b' k" `2 q; h$ a; L3 F" @
Rank correlation, 等级相关8 m5 X4 f" l7 ]' Y
Rank sum test, 秩和检验
3 m! L( c2 [/ v6 N( YRank test, 秩检验/ i; T# E3 K+ }6 w* G& l
Ranked data, 等级资料
3 s4 K" p1 L$ G, n( b+ v/ M7 J/ \& FRate, 比率( B6 @- a8 X$ N" B
Ratio, 比例& _$ M1 {6 @& o: H& B5 {: T
Raw data, 原始资料
) C/ d1 Z; R4 H4 Q$ TRaw residual, 原始残差$ }5 G( i# C/ c1 V/ u
Rayleigh's test, 雷氏检验; o3 d0 h# h" ? C: U
Rayleigh's Z, 雷氏Z值 / G5 W0 U- A1 [+ a# o
Reciprocal, 倒数
8 [0 e @. ]$ B" tReciprocal transformation, 倒数变换2 ?$ R, `) N2 U7 _( b
Recording, 记录
4 t# _* o' ]& D. ~0 d; zRedescending estimators, 回降估计量
, D) ~1 }9 \0 pReducing dimensions, 降维; X( u; L# p+ N# |: V5 C
Re-expression, 重新表达6 ~+ t+ }$ h; x' r9 Y7 i: R
Reference set, 标准组
o5 Y$ n# v$ o9 k' \Region of acceptance, 接受域* E$ `, i! Q# P2 t7 i1 ~
Regression coefficient, 回归系数1 T7 g% i; F0 O& S' B
Regression sum of square, 回归平方和' S% Q7 Y7 K8 H
Rejection point, 拒绝点0 g9 h# e# [. [
Relative dispersion, 相对离散度2 t* t1 P* v5 Z$ @" v
Relative number, 相对数
* D/ a1 V8 l: i) G$ SReliability, 可靠性
* a. c' V% t. `: F- X5 gReparametrization, 重新设置参数
9 z5 ~, l9 G' F+ t$ VReplication, 重复
* v& T6 b; y' G3 Q; s" rReport Summaries, 报告摘要
# Y. a9 W1 N2 ~4 [8 j/ lResidual sum of square, 剩余平方和7 \+ h, E. v% k- r5 A
Resistance, 耐抗性
" i+ J$ G7 }3 C' kResistant line, 耐抗线2 J" {8 q/ p' E. _9 Q8 d8 `* y
Resistant technique, 耐抗技术0 U9 d+ b/ o2 ~8 y* F
R-estimator of location, 位置R估计量
# ^6 D: b) `0 l5 z, M; uR-estimator of scale, 尺度R估计量$ B5 s+ g) Y% E/ d) p. z
Retrospective study, 回顾性调查- S, h! [" x' U& A! w
Ridge trace, 岭迹5 d: R9 _+ u, {
Ridit analysis, Ridit分析
; l( p& A* m% @4 k8 ^3 tRotation, 旋转
2 p+ v2 \+ J: b6 RRounding, 舍入
l$ ]+ H+ R7 z8 X6 XRow, 行
1 S- C; c( e* C: ?7 n4 M: f2 j2 GRow effects, 行效应
N5 V' |# T4 `1 S3 _1 {Row factor, 行因素
$ P$ c, U6 m l. s; lRXC table, RXC表
- ~$ \' P) b% ]Sample, 样本
- ^, m1 K$ I: W! g' I7 dSample regression coefficient, 样本回归系数( S# q) O+ `$ M9 s# X3 q2 Q
Sample size, 样本量6 a4 d2 e2 N& U$ h( p b
Sample standard deviation, 样本标准差
|* i# o3 {' ^ Z. vSampling error, 抽样误差$ c e/ M# I, F3 H6 B
SAS(Statistical analysis system ), SAS统计软件包
" D2 X. S0 y, FScale, 尺度/量表
0 g. H- H6 G4 Y/ gScatter diagram, 散点图
& u, Z3 |5 f6 }, Q5 v( Z: X6 O) uSchematic plot, 示意图/简图# }: x( D! K$ T- ]" h
Score test, 计分检验. }4 K. q1 |+ j) r4 ?! h& O( n0 V3 b
Screening, 筛检
+ U$ {+ f" F+ B/ \6 kSEASON, 季节分析 J' U$ M/ R9 R( z$ h; S
Second derivative, 二阶导数
6 E. @2 H3 j" m% Y. I$ n: I8 S' dSecond principal component, 第二主成分
6 M+ n% I7 F* l: f( M! XSEM (Structural equation modeling), 结构化方程模型
% v+ c! k9 i- s) fSemi-logarithmic graph, 半对数图/ z+ E: o; ]$ ]3 K# \
Semi-logarithmic paper, 半对数格纸7 G8 h3 L4 ?5 C8 g! ~
Sensitivity curve, 敏感度曲线! _% W8 C& d0 c* Y0 U6 k5 _' i
Sequential analysis, 贯序分析
+ r; l# `1 j, u( j& dSequential data set, 顺序数据集
! j) H& l c5 `& x+ Z4 V* lSequential design, 贯序设计
: X2 l9 Y- [; n0 T, E. U* A7 M' RSequential method, 贯序法& I7 m; z! ~% t$ B! I0 a
Sequential test, 贯序检验法
% I9 @6 C/ {- mSerial tests, 系列试验4 I: G# j+ d1 e" ]( a: W( O/ X
Short-cut method, 简捷法 ; b: ~ r) a7 R
Sigmoid curve, S形曲线
6 a$ \4 o! P# ?$ ^Sign function, 正负号函数
. {/ l( z7 z# X& j! M% Y6 BSign test, 符号检验$ D3 T) X* \, j ~1 M% o
Signed rank, 符号秩
( l' ?8 s; O; ~4 p% [/ U% xSignificance test, 显著性检验
) c+ N( }# J) K2 PSignificant figure, 有效数字/ n+ w: I) g1 ^7 {
Simple cluster sampling, 简单整群抽样$ ~$ ]& j6 W0 |8 V5 p" F
Simple correlation, 简单相关
" A r1 ?5 X0 ]Simple random sampling, 简单随机抽样
1 _$ U7 c; x' W. y0 s9 WSimple regression, 简单回归
8 `1 l5 x: m* m0 z1 @$ T' Q0 x. |simple table, 简单表
, c$ S. [$ @: w3 b- G! Z/ B6 mSine estimator, 正弦估计量
$ t& W# j( }& c/ DSingle-valued estimate, 单值估计
. t& k4 Q4 W8 h( vSingular matrix, 奇异矩阵
, d) m1 Z# E! z- o: LSkewed distribution, 偏斜分布8 x$ c0 s9 C- |$ k& ? r$ ~
Skewness, 偏度6 f0 z2 A+ |& f. o
Slash distribution, 斜线分布
# x) G) r- x' u/ U0 K; V4 ]" `Slope, 斜率' t1 h9 T, ^/ `6 w
Smirnov test, 斯米尔诺夫检验( G! U. a! m9 B c* U1 G2 z8 S
Source of variation, 变异来源! B1 o2 |1 a1 V& ]7 {7 n4 |4 j
Spearman rank correlation, 斯皮尔曼等级相关
4 H0 p" r2 G. [$ e0 [$ p" gSpecific factor, 特殊因子
: L" R ~. Q) vSpecific factor variance, 特殊因子方差
( |: s+ l: l3 y6 `( hSpectra , 频谱
8 @& T x! U, D1 n$ ~/ fSpherical distribution, 球型正态分布/ N* q* W' X! n8 m% j
Spread, 展布
; s" m) y7 N2 @SPSS(Statistical package for the social science), SPSS统计软件包6 b( A9 L& _5 ~' b2 S& N
Spurious correlation, 假性相关* F9 @7 {- F- X6 n
Square root transformation, 平方根变换) u! e5 f- M4 {3 p8 S2 N1 u3 \/ o+ c
Stabilizing variance, 稳定方差* l) w! }' t3 H `- U. w4 W! S
Standard deviation, 标准差
2 [; m0 O6 a# {6 g" R, gStandard error, 标准误# R$ c" y4 u4 B( O1 x" E
Standard error of difference, 差别的标准误# v8 r$ q& r4 A' a9 ?" Y
Standard error of estimate, 标准估计误差- E. w5 e, T4 S' _8 k5 q
Standard error of rate, 率的标准误
* J- J% [9 h7 o. J3 w* xStandard normal distribution, 标准正态分布
( X8 D% Z* R# s: C/ e* hStandardization, 标准化
- K2 ?, r8 r) T, r" m0 r7 O: eStarting value, 起始值6 R6 |9 x K8 X; G2 l: J
Statistic, 统计量
# ]7 t* K) m& Y+ YStatistical control, 统计控制# c ~* O7 Z. d* d+ g; b
Statistical graph, 统计图
) M8 O) V, Q0 t/ N- wStatistical inference, 统计推断& n& L- T$ f7 s$ E. T2 ?9 t
Statistical table, 统计表- N; Z/ A' W( V* j, r, b& }
Steepest descent, 最速下降法* Z+ \. P6 `9 d
Stem and leaf display, 茎叶图
0 x7 S$ F5 v8 l. l) v3 G- ~% T6 eStep factor, 步长因子! |5 B$ G |9 U' v% c' d# W" F7 L: b" n
Stepwise regression, 逐步回归" s) q; D" y6 D9 I$ r4 H) K
Storage, 存
* M0 y" i; c7 w% e! iStrata, 层（复数）
' X* p6 ]3 d, _$ J( HStratified sampling, 分层抽样" N7 F6 l) u3 C, Y1 S/ ~
Stratified sampling, 分层抽样; e3 q( P) \8 a
Strength, 强度" U( o0 k( t# w0 E' }3 Y
Stringency, 严密性
: ?! h3 _' t3 eStructural relationship, 结构关系, W" U, p# b3 {/ t
Studentized residual, 学生化残差/t化残差
, z5 |3 _; \4 ^Sub-class numbers, 次级组含量# P# U0 }4 u4 x1 w7 H
Subdividing, 分割7 o2 ~# }0 v* O+ l) r+ _
Sufficient statistic, 充分统计量
! C+ N6 K. v% x& s, h: |0 M& zSum of products, 积和- ~: G9 @+ C1 P$ F0 s8 A5 N3 ?- M
Sum of squares, 离差平方和
: b! X. ~ D' L# eSum of squares about regression, 回归平方和
6 y! L0 M8 D4 n; H, r/ X; bSum of squares between groups, 组间平方和" q5 F% C! T K! s$ d C6 N
Sum of squares of partial regression, 偏回归平方和
1 a( X5 R; F4 t4 eSure event, 必然事件 U' q5 j! u6 F* I" x
Survey, 调查$ y8 k7 c2 a v8 s) H% C" J% ]
Survival, 生存分析6 i# j; L0 Q, g
Survival rate, 生存率
/ R7 h6 b/ |. S( ^% n5 [1 u5 VSuspended root gram, 悬吊根图
! P e. V5 i+ u9 f4 {Symmetry, 对称
, z5 o' `3 N) p8 p1 ~+ d0 Z( nSystematic error, 系统误差' B/ c& v% a; {
Systematic sampling, 系统抽样6 H0 j9 B/ |- f+ Z! K% y
Tags, 标签
/ r5 e" Z# l; v3 E6 n8 F& VTail area, 尾部面积
w+ U: E5 a5 F$ ZTail length, 尾长
0 i, B( [; c2 ?8 N( w. v( t6 @7 a$ ETail weight, 尾重/ f" B1 i7 I. h% k% W: E" g
Tangent line, 切线: [/ O! v* v; ^# O x8 h7 {) ]
Target distribution, 目标分布- ~* r3 @8 N t9 P
Taylor series, 泰勒级数
9 }# k! V6 l2 |% h9 K2 ~Tendency of dispersion, 离散趋势* n( }7 ?% I& n4 \6 S: U* D, O V
Testing of hypotheses, 假设检验$ L `' G3 Q! k* w) W# \
Theoretical frequency, 理论频数
: m# W# S4 R- }$ WTime series, 时间序列
; F# c+ [4 `. R4 d6 O7 {Tolerance interval, 容忍区间
* f6 v( e0 W! j7 }/ ^# vTolerance lower limit, 容忍下限
0 A& N" Z; m! \7 E1 W: jTolerance upper limit, 容忍上限
' Z6 [" n3 p% B8 P" sTorsion, 扰率
7 m$ k# w4 y# G3 J% k4 H8 Z* C vTotal sum of square, 总平方和
7 p* z0 G5 K( U4 ?8 gTotal variation, 总变异# t. Q" ~" x2 P- E* M& a( P
Transformation, 转换: R( N8 x s7 r) x9 g+ `. E' t1 k8 @
Treatment, 处理% Y$ a/ k% a# r( J$ A7 S
Trend, 趋势8 u4 U( c1 T0 \! ?6 i% f
Trend of percentage, 百分比趋势' ` z: G& _* S( L% J
Trial, 试验
( N4 C w& h: S7 s7 h0 b+ fTrial and error method, 试错法
: @: Z2 T9 c: w8 a, @) G4 gTuning constant, 细调常数
1 a" v( F& _! [ DTwo sided test, 双向检验
& o3 }8 f& K2 U4 l/ d! @Two-stage least squares, 二阶最小平方
7 F! k" @7 ]# ?' JTwo-stage sampling, 二阶段抽样
, n7 @) }$ Q/ i }* ]2 X+ _Two-tailed test, 双侧检验) K* {- F! X7 J, W4 O2 K
Two-way analysis of variance, 双因素方差分析( B, m. u' |% U' c6 H
Two-way table, 双向表
1 E$ L* i2 v$ W( Q/ o/ vType I error, 一类错误/α错误 Q7 ?+ R. D3 K; E4 n- T
Type II error, 二类错误/β错误
' o# l+ B" v2 S2 B2 K9 xUMVU, 方差一致最小无偏估计简称
3 g" t* l) m! |6 _Unbiased estimate, 无偏估计
3 m# ?5 z0 q2 o0 h; p" p# O' {Unconstrained nonlinear regression , 无约束非线性回归
3 ^7 Y7 c0 F- o" g$ X% YUnequal subclass number, 不等次级组含量
* A, S0 [2 [) X t8 B# oUngrouped data, 不分组资料
& n, E3 z; y1 y0 ]Uniform coordinate, 均匀坐标& w) x& H! P. \4 D; |' ]% @
Uniform distribution, 均匀分布' \9 h E+ j2 {5 T2 ]
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
1 i c n3 ~3 m8 e2 _Unit, 单元
2 D0 y2 [9 O7 g* s( M+ m% fUnordered categories, 无序分类) x+ g+ u+ Z/ i; s4 h' E
Upper limit, 上限
" \! `! F3 h9 h" a& p1 UUpward rank, 升秩
0 M) n0 ^& W6 ]8 U1 t1 i* O5 PVague concept, 模糊概念
. V6 j) l, t b: ]: }0 I) t, v ZValidity, 有效性
0 F7 _9 P2 t0 F% {VARCOMP (Variance component estimation), 方差元素估计' {3 ?1 @( t9 a; D, N2 \6 Z
Variability, 变异性* @! g. ]9 o" S4 T
Variable, 变量1 G( E" K! |, Q. D5 |
Variance, 方差
7 d( l3 V0 E0 K6 [+ AVariation, 变异1 R+ W' V% X, _
Varimax orthogonal rotation, 方差最大正交旋转- L X3 a' o; J8 }1 `; r
Volume of distribution, 容积
, J$ \1 _; }% N* vW test, W检验
+ x+ t( n" X2 E5 R. `" }$ u l9 G' a; hWeibull distribution, 威布尔分布- O0 E2 b" u: ?8 S" g# _ _& r4 Y5 x
Weight, 权数
1 y5 p# k+ D- ~* p' iWeighted Chi-square test, 加权卡方检验/Cochran检验6 p! w2 ]9 X9 y; i
Weighted linear regression method, 加权直线回归
( i8 q& {$ h, C( _$ a. {Weighted mean, 加权平均数" t; [% {. _! y" u2 z7 w
Weighted mean square, 加权平均方差
: j+ w' J9 R- s8 nWeighted sum of square, 加权平方和$ [) Q. ~; H9 [
Weighting coefficient, 权重系数2 Q3 d4 y) e: W- S4 Z
Weighting method, 加权法 * P4 M F) y/ w/ m; o
W-estimation, W估计量
0 J" L7 S! `4 [! p" _W-estimation of location, 位置W估计量
9 g2 ?" I1 P) iWidth, 宽度- j* |: l8 q' u. |
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
6 p `3 s! f2 ~% u3 o0 DWild point, 野点/狂点
8 W* ]/ H; ?6 ]! b' E' ]Wild value, 野值/狂值
* Y& K4 {; {/ Y9 }) nWinsorized mean, 缩尾均值# s! \# {+ q: |" O$ o
Withdraw, 失访
# y- ?, R' Q s0 c% b4 M' N$ ], Z7 ?; uYouden's index, 尤登指数
9 u, |2 O( ]4 C% o' {+ PZ test, Z检验" I$ S! Y. n e9 H! K
Zero correlation, 零相关
9 d) F8 i* R) Q2 A- pZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
